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Chronic kidney disease (CKD) is a worldwide public health problem which imposes a significant financial burden not only on patients but also on the healthcare systems, especially under the pressure of the rapid growth of the elderly population in China. The purpose of this paper is to examine the hospitalization costs of patients with CKD between two urban health insurance schemes and investigate the factors that were associated with their inpatient costs in Guangzhou, China.

This was a prevalence-based, observational study using data derived from two insurance claims databases during the period from January 2010 to December 2012 in the largest city, Guangzhou in Southern China. The authors identified 5,803 hospitalizations under two urban health insurance schemes. An extension of generalized linear model – the extended estimating equations approach – was performed to identify the main drivers of total inpatient costs.

Among 5,803 inpatients with CKD, the mean age was 60.6. The average length of stay (LOS) was 14.4 days. The average hospitalization costs per inpatient were CNY15,517.7. The mean inpatient costs for patients with Urban Employee-based Basic Medical Insurance (UEBMI) scheme (CNY15,582.0) were higher than those under Urban Resident-based Basic Medical Insurance (URBMI) scheme (CNY14,917.0). However, the percentage of out-of-pocket expenses for the UEBMI patients (19.8 percent) was only half of that for the URBMI patients (44.5 percent). Insurance type, age, comorbidities, dialysis therapies, severity of disease, LOS and hospital levels were significantly associated with hospitalization costs.

The costs of hospitalization for CKD were high and differed by types of insurance schemes. This was the first study to compare the differences in hospitalization costs of patients with CKD under two different urban insurance schemes in China. The findings of this study could provide economic evidence for understanding the burden of CKD and evaluating different treatment of CKD (dialysis therapy) in China. Such useful information could also be used by policy makers in health insurance program evaluation and health resources allocation.

The purpose of this paper is to have a deeper understanding of the nonlinear relationship between the impact of climate change on tourism development. Current studies on the effects of climate change on tourism development primarily rely on linear correlation assumptions.

Based on the New Institutional Economics theory, the institutional setting inherently motivates and ensures the growth of the tourism industry. For a precise evaluation of the nonlinear consequences of climate change on tourism, this paper concentrates on Chinese cities between 2011 and 2021, methodically analyzing the influence of climate change on tourism.

The study findings suggest that there is an “inverse U”-shaped nonlinear relationship between climate change and tourism development, initially strengthening and subsequently weakening. Based on these findings, the research further delves into how institutional contexts shape the nonlinear association between climate change and tourism growth. It was found that in a higher institutional backdrop, the “inverse U” curve tends to flatten and surpass the curve adjusted for a lesser institutional context. Upon deeper mechanism analysis, it was observed that cities with more advanced marketization, improved industrial restructuring and enhanced educational growth exhibit a more evident “inverse U”-shaped nonlinear connection between climate change and tourism evolution.

First, previous studies on climate change and tourism development largely rely on questionnaire data (Hu et al., 2022). In contrast to these studies, this paper uses dynamic panel data, which to some extent overcomes the subjectivity and difficulty of causality identification in questionnaire data, making our research conclusions more accurate and reliable. Second, this study breaks through the linear relationship hypothesis of previous literature regarding climate change and tourism development. By evaluating the nonlinear relationship of climate change to tourism development from the institutional pressure perspective, it more intricately delineates their interplay mechanism, expanding and supplementing the research literature on the relationship mechanism between climate change and tourism development. Thirdly, the conclusions of this study are beneficial for policymakers to better understand and assess the scope of climate change impacts. It also aids relevant departments in clarifying the direction of institutional environment optimization to elevate the level of tourism development when faced with adverse impacts brought about by climate change.

The purpose of this paper is to investigate ways to mitigate gender bias in entrepreneurial financing. The authors aim to unveil the role entrepreneurs’ gender played in formal and informal financing under Chinese context, as well as the moderating role corporate social responsibility (CSR) played in such relationships.

This paper adopts ANOVA test and multiple regression method to empirically examine the relationship of entrepreneurs’ gender, formal financing, informal financing and CSR with second hand data from The Eleventh Private Enterprise Survey covering a sample of firms across China.

The results demonstrate that comparing to start-ups led by men, start-ups led by women are less likely to get either formal or informal financing. The results also suggest that CSR negatively moderates the impact entrepreneurs’ gender has on formal financing but not on informal financing.

By focusing on both formal and informal financing, the research of gender’s effects on firms’ financing has been extended. Also, by proving that CSR can help to mitigate gender bias in formal financing, contribution has also been made to the research field of gender financing. This paper contributes to the CSR literature by sorting out another benefit CSR has in new venture financing. Overall, findings of this study deepen the existing understanding of gender issues in the context of entrepreneurial financing.

When the mobile manipulator is traveling on an unconstructed terrain, the external disturbance is generated. The load on the end of the mobile manipulator will be affected strictly by the disturbance. The purpose of this paper is to reject the disturbance and keep the end effector in a stable pose all the time, a control method is proposed for the onboard manipulator.

In this paper, the kinematics and dynamics models of the end pose stability control system for the tracked robot are built. Through the guidance of this model information, the control framework based on active disturbance rejection control (ADRC) is designed, which keeps the attitude of the end of the manipulator stable in the pitch, roll and yaw direction. Meanwhile, the control algorithm is operated with cloud computing because the research object, the rescue robot, aims to be lightweight and execute work with remote manipulation.

The challenging simulation experiments demonstrate that the methodology can achieve valid stability control performance in the challenging terrain road in terms of robustness and real-time.

This research facilitates the stable posture control of the end-effector of the mobile manipulator and maintains it in a suitable stable operating environment. The entire system can normally work even in dynamic disturbance scenarios and uncertain nonlinear modeling. Furthermore, an example is given to guide the parameter tuning of ADRC by using model information and estimate the unknown internal modeling uncertainty, which is difficult to be modeled or identified.

This paper aims to investigate how information and communication technology (ICT) services and digital finance affect the development of international tourism.

The two-way fixed effect panel regression model, spatial econometric model, panel threshold regression model and panel quantile regression model are used. Data on tourism, economic and social development in 198 Chinese cities from 2011 to 2020 are analyzed.

This study finds that digital economy including ICT services and digital finance has significantly promoted the development of international tourism industry, while there is a negative spatial spillover effect. The promotion effect of international tourism increases significantly after digital innovation reaches the threshold value. International tourism is benefiting more from digital economy with the development of international tourism industry.

The development quality of international tourism industry has not been analyzed due to data limitations, and the mechanism has not been tested.

This study creatively reveals the development of international tourism industry in the digital economy era from ICT services and digital finance perspectives. This study also shows the spatial, nonlinear and asymmetric relationship between digital economy and international tourism.

The government has included social media technology applications in the public sector as part of the fifth wave of information and communications technology adoption. Academic interest in social media in the government sector has been increasing. But there has been little empirical research on the assimilation of social media in the local government. To fill this gap, based on technology–organization–environment (TOE) framework, this study aims to investigate the key technological, organizational and environmental factors that affect the assimilation of social media in local government agencies.

To empirically test the model, a survey study was conducted. Data were collected from 150 government employees in the government department of X municipal government in China. The collected data were analysed quantitatively to answer five hypotheses using structural equation model.

The findings suggest that technology competence, top management support, perceived benefits and citizen readiness significantly influence assimilation of social media in local government agencies. Top management support is the strongest predictor of social media assimilation in a government agency.

This study is one of the first attempts that adopted the TOE framework to understand assimilation of social media in the local government. In addition, the effect of the four factors that include one technological factor, two organizational factors and one environmental factor, namely, technology competence, top management support, perceived benefits and citizen readiness, on intention to assimilate social media was investigated.

The purpose of this study is to investigate the characteristic and function of oxide film formed on grinding wheel in electrolytic in-process dressing (ELID) precision grinding and improve the quality of ELID grinding.

Dynamic film forming experiments were carried out with a simulation device close to the actual processing conditions. Then, the ELID grinding experiments of bearing rings were performed using grinding wheels with good film forming effect. The experiment was designed by quadratic regression general rotation combination method. The influence of grinding depth, electrolytic voltage, duty cycle and grinding wheel linear speed on grinding effect is analyzed.

A mathematical model for the formation rate of oxide film was established. The experiments show that the composition of grinding wheel and grinding fluid, as well as the electrical parameters, influence the film forming effect. Thus, the oxide film plays an important role in ELID grinding.

This study provides a reference for the design and selection of grinding wheel and grinding fluid and the setting of process parameters in ELID grinding.

Objectively evaluating the fairness of the algorithm, exploring in specific scenarios combined with scenario characteristics and constructing the algorithm fairness evaluation index system in specific scenarios.

This paper selects marketing scenarios, and in accordance with the idea of “theory construction-scene feature extraction-enterprise practice,” summarizes the definition and standard of fairness, combs the application link process of marketing algorithms and establishes the fairness evaluation index system of marketing equity allocation algorithms. Taking simulated marketing data as an example, the fairness performance of marketing algorithms in some feature areas is measured, and the effectiveness of the evaluation system proposed in this paper is verified.

The study reached the following conclusions: (1) Different fairness evaluation criteria have different emphases, and may produce different results. Therefore, different fairness definitions and standards should be selected in different fields according to the characteristics of the scene. (2) The fairness of the marketing equity distribution algorithm can be measured from three aspects: marketing coverage, marketing intensity and marketing frequency. Specifically, for the fairness of coverage, two standards of equal opportunity and different misjudgment rates are selected, and the standard of group fairness is selected for intensity and frequency. (3) For different characteristic fields, different degrees of fairness restrictions should be imposed, and the interpretation of their calculation results and the means of subsequent intervention should also be different according to the marketing objectives and industry characteristics.

First of all, the fairness sensitivity of different feature fields is different, but this paper does not classify the importance of feature fields. In the future, we can build a classification table of sensitive attributes according to the importance of sensitive attributes to give different evaluation and protection priorities. Second, in this paper, only one set of marketing data simulation data is selected to measure the overall algorithm fairness, after which multiple sets of marketing campaigns can be measured and compared to reflect the long-term performance of marketing algorithm fairness. Third, this paper does not continue to explore interventions and measures to improve algorithmic fairness. Different feature fields should be subject to different degrees of fairness constraints, and therefore their subsequent interventions should be different, which needs to be continued to be explored in future research.

This paper combines the specific features of marketing scenarios and selects appropriate fairness evaluation criteria to build an index system for fairness evaluation of marketing algorithms, which provides a reference for assessing and managing the fairness of marketing algorithms.

Algorithm governance and algorithmic fairness are very important issues in the era of artificial intelligence, and the construction of the algorithmic fairness evaluation index system in marketing scenarios in this paper lays a safe foundation for the application of AI algorithms and technologies in marketing scenarios, provides tools and means of algorithm governance and empowers the promotion of safe, efficient and orderly development of algorithms.

In this paper, firstly, the standards of fairness are comprehensively sorted out, and the difference between different standards and evaluation focuses is clarified, and secondly, focusing on the marketing scenario, combined with its characteristics, key fairness evaluation links are put forward, and different standards are innovatively selected to evaluate the fairness in the process of applying marketing algorithms and to build the corresponding index system, which forms the systematic fairness evaluation tool of marketing algorithms.

Drawing upon affective events theory and regulatory focus theory, the current study examines the relationship between customer gratitude and customer-oriented organizational citizenship behavior (customer-oriented OCB), and the mediating role of positive affect and the moderating role of trait promotion focus.

Three-wave time-lagged data from 674 nurses nested within 125 department supervisors was collected. Multilevel modeling and Monte Carlo simulation were performed using Mplus 7.1 software to test all hypotheses.

Customer gratitude was positively associated with nurses’ customer-oriented OCB, and the relationship was mediated by positive affect. Nurse trait promotion focus strengthened the positive relationship between patient gratitude and positive affect, such that the relationship was stronger for those with a higher level of trait promotion focus.

This paper extends research on the effects of customer gratitude by extending our understanding of customer gratitude as a positive workplace event that can potentially promote employees’ positive behaviors toward customers, especially those with a stronger promotion focus.

This study is one of the first to examine the relationship between customer gratitude and employee customer-oriented OCB and uncover potential mechanisms to understand how this relationship unfolds and to whom this relationship is stronger. These findings can inform practices for service organizations.

Attention is one of the most important factors to affect the academic performance of students. Effectively analyzing students' attention in class can promote teachers' precise teaching and students' personalized learning. To intelligently analyze the students' attention in classroom from the first-person perspective, this paper proposes a fusion model based on gaze tracking and object detection. In particular, the proposed attention analysis model does not depend on any smart equipment.

Given a first-person view video of students' learning, the authors first estimate the gazing point by using the deep space–time neural network. Second, single shot multi-box detector and fast segmentation convolutional neural network are comparatively adopted to accurately detect the objects in the video. Third, they predict the gazing objects by combining the results of gazing point estimation and object detection. Finally, the personalized attention of students is analyzed based on the predicted gazing objects and the measurable eye movement criteria.

A large number of experiments are carried out on a public database and a new dataset that is built in a real classroom. The experimental results show that the proposed model not only can accurately track the students' gazing trajectory and effectively analyze the fluctuation of attention of the individual student and all students but also provide a valuable reference to evaluate the process of learning of students.

The contributions of this paper can be summarized as follows. The analysis of students' attention plays an important role in improving teaching quality and student achievement. However, there is little research on how to automatically and intelligently analyze students' attention. To alleviate this problem, this paper focuses on analyzing students' attention by gaze tracking and object detection in classroom teaching, which is significant for practical application in the field of education. The authors proposed an effectively intelligent fusion model based on the deep neural network, which mainly includes the gazing point module and the object detection module, to analyze students' attention in classroom teaching instead of relying on any smart wearable device. They introduce the attention mechanism into the gazing point module to improve the performance of gazing point detection and perform some comparison experiments on the public dataset to prove that the gazing point module can achieve better performance. They associate the eye movement criteria with visual gaze to get quantifiable objective data for students' attention analysis, which can provide a valuable basis to evaluate the learning process of students, provide useful learning information of students for both parents and teachers and support the development of individualized teaching. They built a new database that contains the first-person view videos of 11 subjects in a real classroom and employ it to evaluate the effectiveness and feasibility of the proposed model.